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Ocas Praxis
by
Indigo Karasu
· GitHub ↗
· v2.0.0
· MIT-0
206
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2
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Install in OpenClaw
/install ocas-praxis
Description
Bounded behavioral refinement loop. Records outcomes, extracts micro-lessons from repeated patterns, consolidates them into capped active behavior shifts, ap...
Usage Guidance
This skill appears to do what it says: manage a bounded loop of events→lessons→shifts and write auditable journals. Before installing, confirm you are comfortable granting the agent read/write access to ~/openclaw/data/ocas-praxis and ~/openclaw/journals (or set OCAS_ROOT to an isolated directory). Ask the author to update the manifest to declare OCAS_ROOT or required config paths so the required filesystem access is explicit. Review the retention settings (config.json) to avoid persisting sensitive inputs, and ensure any automated handoff (Corvus → intake) comes from trusted sources. If you need stronger assurance, run the skill in an isolated environment or inspect runtime-produced files periodically.
Capability Analysis
Type: OpenClaw Skill
Name: ocas-praxis
Version: 2.0.0
The ocas-praxis skill implements a structured behavioral refinement loop for an AI agent, focusing on recording task outcomes, extracting lessons from patterns, and maintaining a capped set of active behavior shifts. The skill includes explicit safeguards in SKILL.md against identity rewriting, silent safety boundary changes, and unlimited rule accumulation, ensuring all shifts are traceable and auditable via debriefs. No indicators of malicious intent, data exfiltration, or unauthorized execution were found; the self-modification capabilities are bounded and aligned with the stated purpose of performance optimization.
Capability Assessment
Purpose & Capability
The skill's stated purpose (recording events, extracting lessons, proposing/activating behavior shifts, and producing debriefs) matches the commands, data model, and storage layout in the documentation. It legitimately needs read/write access to a dedicated data directory. However, the SKILL.md references OCAS_ROOT and specific data/journal paths while the skill metadata declares no required config paths or env vars — a minor mismatch in the manifest vs runtime docs.
Instruction Scope
Runtime instructions are narrowly scoped: they read intake JSON files from a dedicated intake directory, record events/lessons/shifts into local JSONL files, move processed files to intake/processed, and write per-run journals. There are no network endpoints or instructions to read unrelated system files. This behavior fits the stated purpose.
Install Mechanism
This is an instruction-only skill with no install spec and no code files — lowest-risk install footprint. Nothing is downloaded or written by an installer.
Credentials
The skill declares no required environment variables, but the docs say OCAS_ROOT can override ~/openclaw. The runtime uses filesystem paths under the user's home; that is reasonable for the functionality, but the manifest should explicitly declare OCAS_ROOT (or the required config path) so users know filesystem access will be needed. Also consider that journals and events may contain sensitive context or hashes.
Persistence & Privilege
The skill stores data under its own ~/openclaw/data/ocas-praxis and ~/openclaw/journals/ocas-praxis locations and enforces caps and retention configuration. It does not request always:true, and it does not purport to modify other skills or system-wide configuration. Persistence is scoped to its own directories.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install ocas-praxis - After installation, invoke the skill by name or use
/ocas-praxis - Provide required inputs per the skill's parameter spec and get structured output
Version History
v2.0.0
ocas-praxis 1.1.1
- Added journal output capability: introduced `references/journal.md` and `praxis.journal` command for writing a run summary at the end of each run.
- Clarified scope and inter-skill interfaces, specifying cooperation with Corvus and Dispatch, and improved documentation of responsibility boundaries.
- Updated storage layout and config documentation for new journal directory and OCAS_ROOT override.
- Added specific OKRs and clarified output/retention practices for better audit and quality tracking.
v1.1.0
Summary: Introduces a structured, bounded behavioral refinement loop for agent behavior improvement.
- Adds event recording, micro-lesson extraction, and consolidation into capped active behavior shifts.
- Enforces a strict limit (default 12) on active behavior shifts with merging or replacement mechanisms at cap.
- Provides commands for recording, extracting, activating, expiring, and listing behavior shifts.
- Generates plain-language debriefs and concise runtime briefs containing only active shifts.
- Ensures every behavior shift is traceable to specific recorded events for auditability.
- Incorporates hard constraints to prevent unlimited growth, silent personality changes, or rule duplication.
Metadata
Frequently Asked Questions
What is Ocas Praxis?
Bounded behavioral refinement loop. Records outcomes, extracts micro-lessons from repeated patterns, consolidates them into capped active behavior shifts, ap... It is an AI Agent Skill for Claude Code / OpenClaw, with 206 downloads so far.
How do I install Ocas Praxis?
Run "/install ocas-praxis" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Ocas Praxis free?
Yes, Ocas Praxis is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Ocas Praxis support?
Ocas Praxis is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Ocas Praxis?
It is built and maintained by Indigo Karasu (@indigokarasu); the current version is v2.0.0.
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